Next-generation sequencing (NGS) technologies have given rise to a wealth of knowledge and information about biological systems, specifically in genomics and epigenomics. The majority of next generation sequencing technologies effectively sample small amounts of DNA or RNA that are amplified (i.e., copied) prior to sequencing. While it is well known that the amplification process is not perfect, and that the sequenced read counts can be extremely biased, unfortunately current amplification bias are not adequate. In fact, current bias controlling procedures introduce a dependence of gene expression on gene length. This issue is addressed via a novel procedure that accounts for amplification bias, and is effective in estimating true gene expression independent of gene length.